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Rationale and Objectives: Accurate assessment of fetal head station (FHS) is crucial during labor management to reduce the risk of complications and plan the mode of delivery. Although digital vaginal examination (DVE) has been associated with inaccuracies in FHS assessment, ultrasound (US) evaluation remains dependent on sonographer expertise. This study aimed at investigating the reliability and accuracy of an automatic approach to assess the FHS during labor with transperineal US (TPU)., Materials and Methods: In this prospective observational study, 27 pregnant women in the second stage of labor, with fetuses in cephalic presentation, underwent conventional labor management with additional TPU examination. A total of 45 2D B-mode TPU acquisitions were performed at different FHS, before performing DVE. The FHS was assessed by the algorithm (FHS aut ) on TPU images and by DVE (FHS dig ). The sonographic assessment of FHS by expert sonographer (FHS exp ) on the same TPU acquisition used for the automatic measurement served as gold standard. The performance and accuracy were assessed through Spearman's ρ, the coefficient of determination (R 2 ), root mean square error (RMSE), and Bland-Altman analysis., Results: A strong correlation between FHS aut and FHS exp (ρ = 0.97, p < 0.001) and a high coefficient of determination (R 2 = 0.95) were found. A lower correlation with FHS exp (ρ = 0.66, p < 0.001) and coefficient of determination (R 2 = 0.52) was found for DVE. Moreover, the RMSE reported higher accuracy of FHS aut (RMSE = 0.32 cm) compared to FHS dig (RMSE = 0.97 cm). Bland-Altman analysis showed that the algorithm performed with smaller bias and narrower limits of agreement compared to DVE., Conclusion: The proposed algorithm can evaluate FHS with high accuracy and low RMSE. This approach could facilitate the use of US in labor, supporting the clinical staff in labor management., Competing Interests: Conflict of Interest F. Conversano, M. Di Paola, and S. Casciaro are shareholders of Amolab srl, a National Research Council spin-off company that may or may not benefit from the results of this study., (Copyright © 2024 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

This study aimed to investigate the Diffusion-Tensor-Imaging (DTI) potential in the detection of microstructural changes in prostate cancer (PCa) in relation to the diffusion weight (b-value) and the associated diffusion length l D . Thirty-two patients (age range = 50-87 years) with biopsy-proven PCa underwent Diffusion-Weighted-Imaging (DWI) at 3T, using single non-zero b-value or groups of b-values up to b = 2500 s/mm 2 . The DTI maps (mean-diffusivity, MD; fractional-anisotropy, FA; axial and radial diffusivity, D// and D┴), visual quality, and the association between DTI-metrics and Gleason Score (GS) and DTI-metrics and age were discussed in relation to diffusion compartments probed by water molecules at different b-values. DTI-metrics differentiated benign from PCa tissue ( p ≤ 0.0005), with the best discriminative power versus GS at b-values ≥ 1500 s/mm 2 , and for b-values range 0-2000 s/mm 2 , when the l D is comparable to the size of the epithelial compartment. The strongest linear correlations between MD, D//, D┴, and GS were found at b = 2000 s/mm 2 and for the range 0-2000 s/mm 2 . A positive correlation between DTI parameters and age was found in benign tissue. In conclusion, the use of the b-value range 0-2000 s/mm 2 and b-value = 2000 s/mm 2 improves the contrast and discriminative power of DTI with respect to PCa. The sensitivity of DTI parameters to age-related microstructural changes is worth consideration.

Rationale and Objectives: To investigate the performance of diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in discriminating benign tissue, low- and high-grade prostate adenocarcinoma (PCa)., Materials and Methods: Forty-eight patients with biopsy-proven PCa of different Gleason grade (GG), who provided written informed consent, were enrolled. All subjects underwent 3T DWI examinations by using b values 0, 500, 1000, 1500, 2000, and 2500 s/mm 2 and six gradient directions. Mean diffusivity, fractional anisotropy (FA), apparent kurtosis (K), apparent kurtosis-derived diffusivity (D), and proxy fractional kurtosis anisotropy (KFA) maps were obtained. Regions of interest were selected in PCa, in the contralateral benign zone, and in the peritumoral area. Histogram analysis was performed by measuring mean, 10th, 25th, and 90th (p90) percentile of the whole-lesion volume. Kruskal-Wallis test with Bonferroni correction was used to assess significant differences between different regions of interest. The correlation between diffusion metrics and GG and between DKI and DTI parameters was evaluated with Pearson's test. ROC curve analysis was carried out to analyze the ability of histogram variables to differentiate low- and high-GG PCa., Results: All metrics significantly discriminated PCa from benign and from peritumoral tissue (except for K, KFA p90 , and FA). K p90 showed the highest correlation with GG and the best diagnostic ability (area under the curve = 0.84) in discriminating low- from high-risk PCa., Conclusion: Compared to DTI, DKI provides complementary and additional information about prostate cancer tissue, resulting more sensitive to PCa-derived modifications and more accurate in discriminating low- and high-risk PCa., (Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Purpose: To test the potential ability of mean diffusivity (MD) and fractional anisotropy (FA) in discriminating between PCa of grade group (GG) 1&2, and GGs≥3., Material and Methods: Diffusion Tensor Imaging (DTI) experiments at 3T in a cohort of 38 patients with PCa (fifty lesions in total) were performed, by using different diffusion weights (b values) up to 2500s/mm(2). Gleason score (GS) and GG data were correlated with DTI parameters (MD and FA) estimated in PCa. The relation between DTI measures and GS was tested by the linear correlation analysis (Pearson's coefficient). One-way analysis of variance to check the statistical significance of the difference between GG 1&2 and GGs 3, 4, 5, ≥3 was used. Results were reported for each of the three b-values ranges: 0-800s/mm(2), 0-1500s/mm(2), 0-2500s/mm(2)., Results: A negative correlation was found between MD and GS. The highest linear correlation was observed when the fit was performed with data acquired in the b-values range 0-2500s/mm(2). MD values were significantly different between GG 1&2 and GG=3 and between GG 1&2 and GG ≥3. Moreover this difference is better defined when high b values (higher than b=800s/mm(2)) are used. The specificity, sensitivity and accuracy in the discrimination between GG 1&2 and GG=3 were: 90%, 66.7% and 82.4%, respectively when MD was estimated in the b-values range 0-2500s/mm(2) while these values were 85%, 58.3% and 78.4% when MD was estimated in the b-values range 0-800s/mm(2). Conversely FA did not discriminate between GG 1&2 and GG ≥3, at any investigated b-values range., Conclusion: This study suggests that MD estimation in PCa, obtained from DTI acquired at high b-values, can contribute to the diagnosis and grading of prostate cancer while FA is not a useful parameter for this purpose., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)